Dissecting the role of viruses in marine nutrient cycling: bacterial uptake of D- and L-amino acids released by viral lysis
Bibliographic record
Abstract
Lysis of marine bacteria by viruses releases a range of organic compounds into the environment, including D-and L-amino acids, but the uptake of these compounds by other bacteria is not well characterized. This study determined that Photobacterium sp. strain SKA34 (Gammaproteobacteria) increased in abundance following uptake of D-and L-amino acids from viral lysate of Cellulophaga sp. strain MM#3 (Flavobacteria). Ammonium and dissolved free amino acids were taken up almost to detection limits, suggesting that the C:N ratio of bioavailable organic matter in the lysate was high for Photobacterium sp. growth, thus causing a net uptake of ammonium. In contrast, only 1.51 mol l -1 of the 4.77 mol l -1 of the total dissolved combined amino acids (DCAAs) were taken up, indicating that a fraction of lysate-derived DCAAs were semi-labile or refractory to bacterial uptake. Both D-and L-amino acid uptake rates were approximately proportional to their concentrations, indicating similar availability for each enantiomer and unsaturated uptake rates. These results imply that under high C:N conditions, both D-amino acids (mainly found in bacterial cell walls) and L-amino acids (found in proteins of the rest of the cell) are equally available for bacterial growth, and support arguments that viruses are key players in marine nitrogen cycling.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".